User Acceptance of Information Technology: Research Progress, Current Controversies, and Emerging Paradigms

Fred DavisWalton College of Business

University of ArkansasDecember 8, 2007

Workshop on HCI Research in MIS

Outline• TAM overview and evolution

• TAM metaanalyses

• Paradigms and scientific progress• Current TAM impasse• Gaps and limitations in TAM++ research• Promising directions for TAM research• Cognitive Neuroscience and Neuro – IS

TAM Overview• Problem Statement

– High failure rate of IS implementations• 1980’s IS Implementation Research

– Mixed and inconclusive• Keen 1980 “reference disciplines and cumulative tradition”• TAM

– Theoretical foundations– Psychometrically validated measures

• IT Design Characteristics– Functionality– User Interface

Technology Acceptance Model(TAM)

PerceivedUsefulness

External Behavioral UsageVariables Intention Behavior

Perceivede.g., Training Ease of UseSystem Chars.

(Davis 1989--MISQ; Davis et al. 1989--Mgmt Science)

Summary of Key Findings from Early TAM Research

• Perceived usefulness is key determinant of acceptance

• Perceived ease of use is a secondary determinant (direct and indirect effect on BI)

• TAM compares favorably with other models• TAM is robust across populations, settings,

technologies

TAM Evolution• 1990’s Proliferation• Consolidation

• 1999 antecedents of EOU• 2000 antecedents of Usefulness• 2003 Unified Theory (UTAUT)

• Metaanalyses (2003-2007)• Citations

• 1989 MISQ cited 900+ times• 1989 Mgt Sci cited 750+ times

• TAM in Workshop on HCI in MIS, ICIS

Anchors

Adjustments

PerceivedUsefulness

PerceivedEase of Use

BehavioralIntention

to Use

Experience

TAM

Venkatesh 1999 ISR Determinants of EOU

BehavioralIntentionto Use

PerceivedUsefulness

PerceivedEase of Use

ObjectiveUsability

PerceivedEnjoyment

ComputerPlayfulness

ComputerAnxiety

Perceptionsof External

Control

ComputerSelf-Efficacy

Anchors

Adjustments

1

2

1

3

Notes: “1” indicates that experience moderated the relationship between the two constructs, as expected“2” indicates that experience moderated the relationship, though not expected “3” indicates that experience had a a direct effect on the construct, as expected

1

2

Determinants of EOU

Venkatesh & Davis 2000 Mgt SciDeterminants of Usefulness

ExperiencePerceivedUsefulness

PerceivedEase of Use

Intentionto Use

UsageBehavior

CognitiveInstrumentalProcesses

SocialInfluence

Processes

Technology Acceptance Model

Social Influence Processes

Image

SubjectiveNorm

Voluntarinessof Use

Experience

PerceivedUsefulness

CognitiveInstrumentalProcesses Experience

PerceivedEase of Use

Intentionto Use

UsageBehavior

A

B

C

Cognitive Instrumental Processes

PerceivedUsefulness

SocialInfluence

Processes

Experience

PerceivedEase of Use

Intentionto Use

UsageBehavior

ResultsDemo.

OutputQuality

JobRelevance

Experience

Venkatesh et al 2003 MISQUnified Model

Social Influence

Facilitating Conditions

Complexity Expectancy

Behavioral Intention

Technology Usage

.46***

.18*

.05

.19*

.08

R2 = .41 R2 = .40

.56***

Job Performance Expectancy

.20**

Attitude Toward

Using Tech.

A

B

A

A: 2-way interaction, with experience as moderatorB: 3-way interaction, with experience and voluntariness as moderators

Different Types of Technology

• Individual productivity tools• Groupware• Enterprise systems• E-Commerce• Workflow• Mobile technology

King & He 2006 I&M

• Meta-analysis of 88 studies• “The results show TAM to be a valid and

robust model that has been widely used, but which potentially has wider applicability.”

• Moderators– User types– Usage types

Jeyaraj, et al. 2006 JIT• Metaanalysis of 99 adoption studies

– 48 individual level studies– 51 organizational level studies

• Best individual adoption predictors– Perceived Usefulness– Top Management Support– Computer Experience– User Support– Behavioral Intention

• Best organizational adoption predictions– Top Management Support– External Pressure– Professionalism of IS unit– External Information Sources

• Top Management Support was main linkage between individual and organizational IT adoption

• Identify 10 areas for further exploration

Schepers & Wetzels 2007 I&M

• Metaanalysis of 63 TAM studies• Focused on role of subjective norm• Confirmed original TAM relationships• Large effect sizes of SN

– On usefulness (internalization)– On intention (compliance)

Sun & Zhang 2006 IJHCS• Role of moderating factors in technology acceptance

– Low explanatory power of TAM models (<60%)– Inconsistent relationships found

• 69 studies reviewed• Ten moderating factors in three groups

– Organizational factors (voluntariness, nature of task and profession)

– Technology factors (complexity, purpose, individual vs. group)

– Individual factors (gender, intellect, experience, age, culture)

• Moderators increase explanatory power

Sabherwal et al 2006 Mgt Sci• Individual and organizational determinants• Metaanalysis of 121 studies• Integrated, emergent model

– Top mgmt support– Facilitating conditions– User experience, attitude, training, participation– System Quality– Perceived usefulness– User satisfaction– System use

• Consistent with prior research on technology adoption and use

Scientific Progress

Every scientific truth goes through three states:

first, people say it conflicts with the Bible; next, they say it has been discovered beforelastly, they say they always believed it.

Louis Agassiz

Nature of Scientific Progress• Role of Paradigms (e.g., Kuhn 1962)

• Container (how much can it hold)• Vehicle (how far can it go? How fast?)• Advantage – enables research progress• Disadvantage – constrains research progress

• Theory can obstruct research progress• Selective filter, lens• Confirmation bias

• Revolution vs. Evolution• Parsimony, Power, Generality

TAM Research Impasse

• JAIS Special Issue April 2007– Lucas, Swanson, & Zmud “Implementation…”– Benbasat & Barki “Quo Vadis, TAM?”

• Proliferation of ad hoc incremental extensions with no overarching conceptual structure

• Successive studies that provide diminishing marginal contributions

• IS researchers’ attention being overly restricted to minor extensions of TAM

“Restlessness and discontent are the first necessities of progress. “

Thomas Edison

Recommended Directions for TAM

• Benbasat & Barki• Go back to TRA/TPB• Better conceptualization of system usage• Longitudinal, multi-stage models• Impact of IT design characteristics• Objective usefulness

• Bagozzi• Goal self-regulation• Group, cultural, social aspects• Emotions

Return to TRA/TPB?

• Benbasat &Barki 2007 JAIS advocate this– Claim that UTAUT does this– Provides structure for expanding TAM

• Pavlou & Fygenson 2006 MISQ– B2C top beliefs elicited

• Usefulness, ease of use, trust– TPB omits direct influence of beliefs on BI

• Bagozzi 2007 JAIS– TPB has many same limitations as TAM

Usage Reconceptualizations• Beyond frequency & duration• Burton-Jones & Straub 2006 ISR

• User-System-Task• Cognitive Absorption• Deep structure usage (task-relevant feature use)• Objective performance

• Barki et al 2007 ISR• Task-technology-individual• Hierarchical goal-oriented actions• Task-technology adaption• Individual adaption

Three Key Limitations of TAM++ Paradigm

• Static, cross-sectional, snapshot-oriented– Individual level of analysis– Limited span across causal chain

• Emphasis on controlled, conscious processing– Exclusion of automatic processing– Overlook multitasking

• Limited account of social processes– Knowledge collaboration– Collective processes

Longer span across causal chain:Wixom & Todd 2005 ISR

• Theoretical Integration of User Satisfaction and Technology Acceptance

• Bridge from design and implementation of system characteristics (a strength of the user satisfaction literature) to prediction of usage (a strength of the TAM literature)

Venkatesh 2006 Dec Sci• Business process change; process standards

• Business process characteristics• Interventions (e.g., simulation based training)

• Supply-chain technologies• Multi-stakeholder technologies• Interventions to reduce goal incongruence and

information assymetry

• Services• Service quality, failure, recovery• Service design characteristics

Major Theoretical Extensions of TAM

• Principal-Agent Theory– Ba, et al. 2001 Mgt Sci; Bhattacherjee 1998 Dec

Sci; Pavlou et al 2007

• Multi-level studies of adoption– Lapointe & Rivard 2005 MISQ, 2007 ISR; Frambach

& Schillewaert 2002 J. Bus Res; Gopalakrishnan, et al. IEEE TEM

• Longitudinal multi-stage modeling– Kim et al 2006 Mgt Sci

Devaraj & Kohli 2005 Mgt Sci

• Performance Impacts of Information Technology: Is Actual Usage the Missing Link?

• “actual usage” may be a key variable in explaining the impact of technology on performance…omittion of this variable may be a missing ling in IT payoff analyses

Automaticity and Multitasking

• TAM++ models presume conscious processing– Conscious intentions and beliefs– Theory of Reasoned Action/Planned Behavior

• Cognitive skill acquisition• Habit versus intention

– Intention-behavior relationship weakens with habit

– Habits toward previous behavior can undermine intentions to adopt new behavior

Dual Processing and Economics• Daniel Kahneman 2002

– Two modes of cognitive processing• System 1 (intuition) – fast, automatic, effortless, associative,

difficult to modify• System 2 (reasoning) – slower, serial, effortful, deliberately

controlled, rule-governed, flexible• Vernon Smith 2002

– “human activity is diffused and dominated by unconscious, autonomic, neuropsychological systems that enable people to function effectively without calling upon the brain’s scarcest resource – attentional and reasoning circuitry”

Automaticity in IS Research

• Habit in IS Continuance• Mindfulness-Mindlessness Paradox

– Butler & Gray 2006 MISQ• Routine-based reliability• Mindfulness-based reliability• Individual and collective mindfulness

Dual-Task Interference

• Primary task demands most attention• Secondary task can be performed with limited

attention• Bottlenecks, working memory load• Task and tool as dual tasks• Electronic brainstorming

– Heninger et al 2006 ISR

Neuro-IS

• Dimoka, Pavlou, & Davis 2007 ICIS– “The potential of cognitive neuroscience for IS

Research”– Neural underpinnings of cognitive processes– Brain scanning (fMRI, etc.)

– Many recent discoveries• Decision making, risk, uncertainty• Trust, cooperation, competition• Goal self-regulation• Automaticity and multitasking

Major Areas of the Brain

A

ACC

NA

CN

IC

PCC

Limbic System

OBF

Prefrontal Cortex

DLPFC

MPFC

iPC

VMPFC

H

DLPFC: Dorsolateral Prefrontal Cortex, VMPFC: Ventromedial Prefrontal Cortex, OBF: Orbitofrontal CortexMPFC: Medial Prefrontal Cortex, ACC/PCC: Anterior/ Posterior Cingulate Cortex, NA: Nucleus Accumbens;A: Amygdala, H: Hippocampus, CN: Caudate Nucleus, IC: Insular Cortex, iPC: Inferior Parietal Cortex

Motor Cortex

Visual Cortex

Cerebellum

Brain StemOther key areas

Brain Areas Activated for Focal Processes

Brain Area

Process

Dorsolateral Prefrontal

Cortex

Ventromedial Prefrontal

Cortex

Orbitofrontal Cortex

Medial Prefrontal

Cortex

Limbic System

AmygdalaAnterior

Cingulate Cortex

Nucleus Accumbens

Caudate Nucleus

Insular Cortex

Inferior Parietal Cortices

Decision Making X X X X X

Risk X

Uncertainty X X

Ambiguity X X X X

Loss X

Rewards X X X X X

Consumer Behavior X X X X

Theory of MindX X

Trust X

Distrust X X

Cooperation X

Competition X X

Neuro-IS and TAM++ Research

• Neural correlates of perceived usefulness and ease of use

• Social influence processes and “theory of mind”

• Automaticity and habit• Goal Self-regulation• Emotional processes

Genetic Epistemology and Piaget’s Philosophy of Science

• Piaget (vs. Kuhn) on Scientific Progress– J.Y. Tsou 2006 Theory and Research

• Continuity vs. discontinuity• Series of successive approximations to truth• Equilibration

– Assimilation and accommodation of existing knowledge structures (reorganization)

• Progress as integrative, cumulative process

Summary• Reaching the limits of TAM++ paradigm

– Need to identify and remove limitations of TAM++ paradigm

• Emphasize impact of IT design characteristics• Integrate across levels of analysis

– From static to dynamic analyses of complex adoption processes

• Neuro-IS• Build upon and go beyond accumulated

knowledge

“However much our knowledge of human behavior falls short of our need for such knowledge, still it is enormous”

Herbert Simon 1978